메뉴 건너뛰기




Volumn , Issue , 2002, Pages

Incorporating invariances in nonlinear support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

DIGIT RECOGNITION; FEATURE SPACE; IMPROVE PERFORMANCE; NONLINEAR KERNELS; NONLINEAR SUPPORT VECTOR MACHINES; PRIOR KNOWLEDGE; SUPPORT VECTOR METHOD; TRANSFORMATION INVARIANCE;

EID: 84898955987     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (15)
  • 1
    • 0002615660 scopus 로고    scopus 로고
    • Geometry and invariance in kernel based methods
    • B. Scholkopf, C. J. C. Purges, and A. J. Smola, editors, MIT Press
    • C. J. C. Purges. Geometry and invariance in kernel based methods. In B. Scholkopf, C. J. C. Purges, and A. J. Smola, editors, Advances in Kernel Methods - Support Vector Learning. MIT Press, 1999.
    • (1999) Advances in Kernel Methods - Support Vector Learning
    • Purges, C.J.C.1
  • 4
    • 34249753618 scopus 로고
    • Support vector networks
    • C. Cortes and V. Vapnik. Support vector networks. Machine Learning, 20:273 - 297, 1995.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 5
    • 0003288005 scopus 로고    scopus 로고
    • Training invariant support vector machines
    • In press
    • D. DeCoste and P. Scholkopf. Training invariant support vector machines. Machine Learning, 2001. In press.
    • (2001) Machine Learning
    • De Coste, D.1    Scholkopf, P.2
  • 6
    • 0008847393 scopus 로고
    • From data distributions to regularization in invariant learning
    • The MIT Press
    • Todd K. Leen. From data distributions to regularization in invariant learning. In NIPS, volume 7. The MIT Press, 1995.
    • (1995) NIPS , vol.7
    • Leen, T.K.1
  • 7
    • 0032203371 scopus 로고    scopus 로고
    • Incorporating prior information in machine learning by creating virtual examples
    • November
    • P. Niyogi, T. Poggio, and F. Girosi. Incorporating prior information in machine learning by creating virtual examples. IEEE Proceedings on Intelligent Signal Processing, 86(2):2196-2209, November 1998.
    • (1998) IEEE Proceedings on Intelligent Signal Processing , vol.86 , Issue.2 , pp. 2196-2209
    • Niyogi, P.1    Poggio, T.2    Girosi, F.3
  • 8
    • 0003243224 scopus 로고    scopus 로고
    • Probabilities for support vector machines
    • A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans, editors, MIT Press, Cambridge, MA
    • John Piatt. Probabilities for support vector machines. In A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans, editors, Advances in Large Margin Classi-fiers. MIT Press, Cambridge, MA, 2000.
    • (2000) Advances in Large Margin Classifiers
    • Piatt, J.1
  • 10
    • 84902142380 scopus 로고    scopus 로고
    • Incorporating invariances in support vector learning machines
    • volume 1112, Berlin, Springer Lecture Notes in Computer Science
    • B. Scholkopf, C. Burges, and V. Vapnik. Incorporating invariances in support vector learning machines. In Artificial Neural Networks - ICANN'96, volume 1112, pages 47-52, Berlin, 1996. Springer Lecture Notes in Computer Science.
    • (1996) Artificial Neural Networks - ICANN'96 , pp. 47-52
    • Scholkopf, B.1    Burges, C.2    Vapnik, V.3
  • 11
    • 51749084180 scopus 로고    scopus 로고
    • Prior knowledge in support vector kernels
    • MIT Press, editor
    • B. Schdlkopf, P. Y. Simard, A. J. Smola, and V. N. Vapnik. Prior knowledge in support vector kernels. In MIT Press, editor, NIPS, volume 10, 1998.
    • (1998) NIPS , vol.10
    • Schdlkopf, B.1    Simard, P.Y.2    Smola, A.J.3    Vapnik, V.N.4
  • 12
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Scholkopf, A. Smola, and K.-R. Miiller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1310, 1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1310
    • Scholkopf, B.1    Smola, A.2    Miiller, K.-R.3
  • 13
    • 0005031076 scopus 로고    scopus 로고
    • Transformation invariance in pattern recognition, tangent distance and tangent propagation
    • G. Orr and K. Muller, editors, Springer
    • P. Simard, Y. LeCun, J. Denker, and B. Victorri. Transformation invariance in pattern recognition, tangent distance and tangent propagation. In G. Orr and K. Muller, editors, Neural Networks: Tricks of the trade. Springer, 1998.
    • (1998) Neural Networks: Tricks of the Trade
    • Simard, P.1    LeCun, Y.2    Denker, J.3    Victorri, B.4
  • 14
    • 0142032204 scopus 로고    scopus 로고
    • Support vector classifier with asymmetric kernel function
    • M. Verleysen, editor
    • K. Tsuda. Support vector classifier with asymmetric kernel function. In M. Verleysen, editor, Proceedings of ESANN'99, pages 183-188, 1999.
    • (1999) Proceedings of ESANN'99 , pp. 183-188
    • Tsuda, K.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.